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夏晓天, 王斌, 张立明. 基于推广的IHS变换和压缩传感的遥感图像融合[J]. 计算机辅助设计与图形学学报, 2013, 25(9): 1399-1409.
引用本文: 夏晓天, 王斌, 张立明. 基于推广的IHS变换和压缩传感的遥感图像融合[J]. 计算机辅助设计与图形学学报, 2013, 25(9): 1399-1409.
Xia Xiaotian, Wang Bin, Zhang Liming. Remote Sensing Image Fusion Based on Generalized IHS Transformation and Compressive Sensing[J]. Journal of Computer-Aided Design & Computer Graphics, 2013, 25(9): 1399-1409.
Citation: Xia Xiaotian, Wang Bin, Zhang Liming. Remote Sensing Image Fusion Based on Generalized IHS Transformation and Compressive Sensing[J]. Journal of Computer-Aided Design & Computer Graphics, 2013, 25(9): 1399-1409.

基于推广的IHS变换和压缩传感的遥感图像融合

Remote Sensing Image Fusion Based on Generalized IHS Transformation and Compressive Sensing

  • 摘要: 为了提高全色图像和多光谱图像的融合图像的质量,提出一种基于推广的intensity-hue-saturation (GIHS)变换和压缩传感的遥感图像融合方法.首先对低分辨率多光谱图像作GIHS变换得到低分辨率的亮度分量;然后在低分辨率的亮度分量、全色图像和理想的高分辨率亮度分量之间建立压缩传感模型;再利用压缩传感理论恢复出理想的高分辨率亮度分量,并用其代替GIHS变换方法中的全色图像,得到最终的融合图像.高分辨率亮度分量的应用,使得融合图像的光谱失真问题大为改善.以Geoeye-1和QuickBird卫星数据为例的实验结果表明,与传统方法相比,文中方法不仅能够提高多光谱图像的空间分辨率,而且对光谱信息的保持也具有更好的效果.

     

    Abstract: In order to improve the quality of the images fused between panchromatic and multispectral images, a remote sensing image fusion algorithm based on generalized intensity-hue-saturation (GIHS) transformation and compressive sensing is proposed in this paper.Firstly, low-resolution intensity component of low-resolution multispectral images is obtained by GIHS transformation.Then, compressive sensing model from high-resolution intensity component to low-resolution intensity component and high-resolution panchromatic image is constructed.Consequently the high-resolution intensity component is recovered by using the compressive sensing theory.Finally, panchromatic image in the GIHS-based fusion method is substituted by the recovered high-resolution intensity component, and the fused multispectral images are obtained.With the high-resolution intensity component, the spectral distortion of the fused images is reduced greatly.The proposed algorithm is tested on Geoeye-1and QuickBird images.The experimental results show that, compared with traditional methods, the proposed algorithm not only improve spatial resolution of the multispectral images but also keep the spectral information better.

     

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